The theory of wavelet packet is more complex than the analysis of wavelet, but its means of analysis is more flexible, and has more accurate partial analysis ability.
小波包理论比小波分析更为复杂，但其分析手段更为灵活，具有更为精确的局部分析能力。
The result shows that the filtering algorithm based on wavelet packet analysis can decrease the random error and improve the measuring precision of laser gyro effectively.
结果表明基于小波包分析的滤波方法能有效减小随机误差，提高激光陀螺的测量精度。
Then, the damage location can be identified by the change of the wavelet packet component energy.
通过各频段能量的变化进行损伤位置的识别。
In traditional denoising methods for signals, we usually use the method of threshold to achieve denoising by the threshold disposing of wavelet packet transform.
传统信号去噪方法常采用门限法对噪声信号的小波或小波包变换做阈值处理以达到去噪的目的。
During detection of asynchronous motor rotor-bar broken fault, the signal of current was reconstruct after decomposed by best wavelet packet and adaptive filtered.
在异步电机转子断条故障检测中，将原信号最优小波包分解，经自适应滤波后再信号重构。
A new method to diagnose faults for high voltage circuit breakers is presented in the paper based on the introduction of wavelet packet and characteristic entropy.
在详细介绍小波包与特征熵的基础上，将二者结合提出了一种诊断高压断路器机械故障的新方法，并给出了切实可行的诊断步骤和分析。
The essence of wavelet packet analysis is to make further decomposition of wavelet decomposed result, so the analysis will yield much better frequency localization.
小波包分析的实质是对小波分解的结果作进一步细分，因而具有比小波分解高得多的频域分辨能力。
To diagnose accurately the rotation machine fault, this paper presents a new method of fault diagnosis based on wavelet packet energy eigenvector and neural network.
为精确诊断旋转机械的故障，提出一种基于小波包特征向量的神经网络故障诊断方法。
In this paper, wavelet packet analysis algorithm is used to extract the characteristics of the cooling fan of inverter and a feature table of typical fault is built.
利用小波包分析算法提取某大型变频器风机的故障特征向量，并构建了典型故障特征表。
The wavelet packet method characterized by good time-frequency localization can be used to make signal reconstruction and energy analysis of blasting vibration wave.
利用小波分析良好的时频局部化性质，可以很好地对爆破地震波进行信号重构和能量分析。
To diagnose accurately vortex rope in draft tube of hydraulic turbine, this paper presents a new method of fault diagnosis based on wavelet packet and neural network.
为精确诊断水轮机尾水管涡带，该文提出一种基于小波包特征熵的神经网络故障诊断新方法。
After noise reduction in the signal, using "wavelet packet-energy" to extract the characteristic vector and input them to the neural network for fault identification.
在对采集到的信号降噪后，利用“小波包-能量”法提取特征量，并将其输入到神经网络中进行故障识别。
Wavelet packet theory is employed to adaptive multiuser detection, and wavelet packet transform based adaptive multiuser detection algorithm is presented in this paper.
在分析传统自适应多用户检测的基础上，提出了一种基于小波包变换的自适应多用户检测算法。
Finally, the wavelet packet histogram is computed as feature signatures and histogram intersection distance is employed to retrieval queried image from image databases.
最后，抽取小波包直方图作为特征表示并应用直方图相交距离从图像数据库中检索被查询图像。
And then, the real-time structural damage detection technology is studied based on wavelet packet analysis. The method is applied to detect simple-supported beam cracks.
然后研究了基于小波包分析的结构实时损伤检测技术，并以简支梁裂缝为例说明。
To solve the problem in obtaining bearing fault characteristics of induction motors, a method based on instantaneous power decomposition via wavelet packet is put forward.
针对感应电动机轴承故障特征提取的不足，提出了瞬时功率小波包分解的方法。
A filter is designed based on wavelet packet according to the features of numerical integral errors and those of multiple scales and high resolving power of wavelet packet.
根据数值计算误差的特点分析及小波包多尺度、高分辨的特性，设计了一种基于小波包的滤波器，较好地解决了消除数值积分计算引入误差的问题。
A wavelet packet frequency-shift algorithm for remote sensing image fusion was introduced to solve the problem of serious frequency aliasing caused by dyadic-down sampling.
在基于小波包的遥感图像融合应用中，引入用于调整小波包分解频率顺序的小波包移频算法来解决由于间隔采样而导致的频带混叠现象。
This paper is mainly concerned with extracting effective features from the recognized or classified signals by selecting wavelet packet basis via given training sample sets.
本文主要研究由给定的训练样本集，如何选择最优小波包基，从被识别或分类的信号中提取具有最大可分性的特征。
Because the wavelet packet decomposition is very sensitive to signal of the strange point, this characteristics can be used to follow the velocity signal of motor vibration.
小波包分解本身对信号的奇异点十分敏感，此特点可以用来跟踪电机振动速度信号。
A new dynamic detection method for roll bearing faults was proposed based on wavelet packet and cross entropy from the angles of information differences of detection signals.
将小波包变换和迭代交叉信息熵有机结合，从检测信号信息量差异性的角度出发，提出一种设备故障动态检测的新方法。
According to the method, the energy of different frequency bands after wavelet packet decomposition constitutes the input vectors of support vector machine as feature vectors.
该方法将振动信号小波包分解后的频带能量作为特征向量，输入到由多个支持向量机构成的多故障分类器中进行故障识别和分类。
Finally, the forecasting results of chaotic models are reconstructed based on the wavelet packet theory and the forecasting result of the original time series can be obtained.
再将混沌模型预测的结果进行小波包重构，则得到原始时序的预测结果。
Approximate coefficients in low frequency band of two images and the average over absolute wavelet packet coefficients of high frequency brand form a fused coefficients matrix.
对两幅图像低频波段的逼近系数取均值，对高频段选取绝对值大的小波包系数，得到融合系数矩阵。
This paper achieves noise reduction by using wavelet packet transform, semisoft shrinkage function, Donoho standard deviation estimate and threshold obtain based on statistics.
计算结果表明：变形统计值与变形监测值吻合较好，统计复相关系数较大，估计标准误差较小。
Then it discusses several transform methods, such as continuous wavelet transform, discrete wavelet transform and wavelet packet transform of which characteristics are analyzed.
然后探讨了连续小波变换、离散小波变换、小波包变换等小波理论中几种重要的变换方法，分析了这几种小波变换的时频特性。
Then, wavelet packet was used to decompose and de-noise the milling force signal, as well as extracts the signals 'energy characteristics as import vectors of BP Neural Network.
然后，采用小波包对采集的铣削力信号进行分解和消噪处理，并提取其能量特征作为BP神经网络的输入向量。
The L F signals are transformed by entropy based on wavelet packet algorithms for best basis selection, and the results are displayed in time- frequency space namely phase plane.
该方法采用基于熵的小波包最佳基选取准则，对局部损伤信号进行自适应小波包分解，将分解结果显示于时—频空间即相平面上。
For wideband noise interferences, this dissertation studies wavelet packet threshold method and USES it to suppress wideband noise interferences in signal domain and image domain.
对于宽带噪声干扰，本文研究了小波包阈值方法，并将之应用到信号域和图像域来抑制宽带噪声干扰。
First the zero sequence transient current signal sampled is enhanced, and then the signal enhanced is decomposed by using wavelet packet analysis to realize faulty line detection.
首先对采样的零序暂态电流信号做增强处理，然后利用小波包分析方法进行故障选线。
应用推荐